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Grains3D, a flexible DEM approach for particles of arbitrary convex shape—Part III: extension to non-convex particles modelled as glued convex particles

Computational Particle Mechanics volume 6, pages 55–84 (2019)Cite this article

Abstract

Large-scale numerical simulation using the discrete element method (DEM) contributes to improving our understanding of granular flow dynamics involved in many industrial processes and geophysical flows. In industry, it leads to an enhanced design and an overall optimization of the corresponding equipment and process. Most of the DEM simulations in the literature have been performed using spherical particles. A limited number of studies dealt with non-spherical particles, even less with non-convex particles. Even convex bodies do not always represent the real shape of certain particles. In fact, more complex-shaped particles are found in many industrial applications, for example, catalytic pellets in chemical reactors or crushed glass debris in recycling processes. In Grains3D-Part I (Wachs et al. in Powder Technol 224:374–389, 2012), we addressed the problem of convex shape in granular simulations, while in Grains3D-Part II (Rakotonirina and Wachs in Powder Technol 324:18–35, 2018), we suggested a simple though efficient parallel strategy to compute systems with up to a few hundreds of millions of particles. The aim of the present study is to extend even further the modelling capabilities of Grains3D towards non-convex shapes, as a tool to examine the flow dynamics of granular media made of non-convex particles. Our strategy is based on decomposing a non-convex-shaped particle into a set of convex bodies, called elementary components. We call our method glued or clumped convex method, as an extension of the popular glued sphere method. Essentially, a non-convex particle is constructed as a cluster of convex particles, called elementary components. At the level of these elementary components of a glued convex particle, we employ the same contact detection strategy based on a Gilbert–Johnson–Keerthi algorithm and a linked-cell spatial sorting that accelerates the resolution of the contact, that we introduced in [39]. Our glued convex model is implemented as a new module of our code Grains3D and is therefore automatically fully parallel. We illustrate the new modelling capabilities of Grains3D in two test cases: (1) the filling of a container and (2) the flow dynamics in a rotating drum.

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Acknowledgements

We would like to thank Prof. Neil Balmforth, University of British Columbia, Canada, for giving us access to his rotating drum experimental set-up and for providing assistance to conduct the experiments. We also would like to acknowledge the help and continuous support of Dr. Abdelkader Hammouti, IFP Energies nouvelles, France, in sharpening up this paper.

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Authors and Affiliations

  1. Fluid Mechanics Department, IFP Energies nouvelles, Rond-point de l’Echangeur de Solaize, BP 3, 69360, Solaize, France

    Andriarimina Daniel Rakotonirina

  2. Department of Mathematics, University of British Columbia, 1984 Mathematics Road, Vancouver, BC, V6T 1Z4, Canada

    Andriarimina Daniel Rakotonirina & Anthony Wachs

  3. Department of Chemical and Biological Engineering, University of British Columbia, 2360 East Mall, Vancouver, BC, V6T 1Z3, Canada

    Anthony Wachs

  4. IATE, UMR 1208 INRA – CIRAD – Montpellier Supagro, Université Montpellier 2, 2 place Pierre Viala, 34060, Montpellier Cedex, France

    Jean-Yves Delenne

  5. CNRS, LMGC UMR 5508, University Montpellier 2, Place Eugène Bataillon, 34095, Montpellier Cedex, France

    Farhang Radjai

  6. MultiScale Material Science for Energy and Environment, UMI 3466 CNRS-MIT, DCEE, Massachusetts Institute of Technology, 77 Massachusetts Avenue, Cambridge, CA, 02139, USA

    Farhang Radjai

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  1. Andriarimina Daniel Rakotonirina
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  2. Jean-Yves Delenne
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  3. Farhang Radjai
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  4. Anthony Wachs
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Correspondence to Anthony Wachs.

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Rakotonirina, A.D., Delenne, JY., Radjai, F. et al. Grains3D, a flexible DEM approach for particles of arbitrary convex shape—Part III: extension to non-convex particles modelled as glued convex particles. Comp. Part. Mech. 6, 55–84 (2019). https://doi.org/10.1007/s40571-018-0198-3

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  • DOI: https://doi.org/10.1007/s40571-018-0198-3

Keywords

  • Granular flow
  • Discrete element method
  • Non-convex shape
  • GJK algorithm
  • Glued convex